Abstract Understanding the spatial and temporal variability of extreme precipitation is critical for climate risk anticipation and long-term adaptation in semi-arid and Mediterranean regions such as Morocco, where hydrological extremes pose major challenges to water resource governance. This study introduces an integrated analytical framework combining standardized indices from the Expert Team on Climate Change Detection and Indices (ETCCDI), Principal Component Analysis (PCA), and Fuzzy C-Means (FCM) clustering to classify extreme precipitation regimes across 38 meteorological stations over the 1989–2018 period. A composite typology was constructed by intersecting wet and dry cluster results, while temporal dynamics were evaluated using the Multivariate Global Climate Typology Index (MGCTI) and a standardized Regional Index (RI). Non-parametric trend detection techniques, including the Mann–Kendall test and Sen’s slope estimator, were applied to assess the direction and magnitude of precipitation changes. Five coherent precipitation regimes were identified, including Wet Dominance, Dry Dominance, and three transitional profiles reflecting structural climatic gradients. Although no significant monotonic trends emerged over the entire study period, decadal analyses revealed intensified dryness post-2009 in arid regions, weakened humid signals in wet zones, and increased variability in transitional areas. This hybrid classification and trend-monitoring approach enhances the detection of emerging hydro-climatic risks and provides region-specific insights for climate adaptation. It also supports prospective climate risk management by identifying early signals of evolving precipitation regimes in vulnerable and transitional areas.
Mounia El Hafyani (Fri,) studied this question.